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reemas-irasna/
home-decor_LoRA

Name: home-decor_LoRA
Availability: InStock

stable-diffusion-xl-diffusers

stabilityai/stable-diffusion-xl-base-1.0

adapter

openrail++

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Using Stable Diffusion XL 1.5, trained a custom model for image generation of Home Decor usecase Also applied Canny ControlNets to it for better performance.

Training Notebook - https://www.kaggle.com/code/reemasirasna/sdxl-training-decor

ControlNet Notebook - https://www.kaggle.com/code/reemasirasna/sdxl-controlnet-decor

Below are the generated images from this model.

SDXL LoRA DreamBooth - reemas-irasna/home-decor_LoRA

Model description

These are reemas-irasna/home-decor_LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.

The weights were trained using DreamBooth.

LoRA for the text encoder was enabled: False.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.

Trigger words

You should use "a photo of home" to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Intended uses & limitations

How to use

python

import torch
from diffusers import DiffusionPipeline, AutoencoderKL

vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0",
    vae=vae,
    torch_dtype=torch.float16,
    variant="fp16",
    use_safetensors=True
)
pipe.load_lora_weights("reemas-irasna/home-decor_LoRA")
_ = pipe.to("cuda")

prompt = "a photo of bedroom in red and white combination"

image = pipe(prompt=prompt, num_inference_steps=25).images[0]
image